DPXPlain: Privately Explaining Aggregate Query Answers

Summary: DPXPlain is a three-phase system for privately explaining group-by aggregate answers under differential privacy. It DP-answers queries, detects whether DP noise flips group comparisons, and outputs a top-k explanation table with predicate influences and confidence intervals, all DP-protected. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 12983
Venue: VLDB
Year: 2023
Pagerank: 4.2815042e-05
Overall Rank: 9,768 | 32.12%
DOI: 10.14778/3561261.3561271

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 7 of 7 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
6,565	Toward Interpretable and Actionable Data Analysis with Explanations and Causality	2022	VLDB	5.0033542e-05
7,172	Summarized Causal Explanations For Aggregate Views	2024	SIGMOD	4.8068645e-05
9,644	Fair and Actionable Causal Prescription Ruleset	2025	SIGMOD	4.3067693e-05
10,015	Differentially Private Explanations for Clusters	2026	SIGMOD	4.1905499e-05
10,147	Causal Explanations for Disparate Trends: Where and Why?	2026	SIGMOD	4.1905499e-05
10,747	Finding Convincing Views to Endorse a Claim	2025	VLDB	4.1905499e-05
11,283	Explaining Differentially Private Query Results With DPXPlain	2023	VLDB	4.1905499e-05

Outgoing Citations (Sorted by Pagerank)

Showing 32 of 32 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
31	Provenance Semirings	2007	PODS	0.00078516827
83	Privacy Integrated Queries: An Extensible Platform for Privacy-Preserving Data Analysis	2009	SIGMOD	0.00053910987
213	Scorpion: Explaining Away Outliers in Aggregate Queries	2013	VLDB	0.0003371037
451	Towards Practical Differential Privacy for SQL Queries	2018	VLDB	0.00022807098
487	Why Not?	2009	SIGMOD	0.00022030123
653	On the Provenance of Non-Answers to Queries over Extracted Data	2008	VLDB	0.00018616975
943	A Formal Approach to Finding Explanations for Database Queries	2014	SIGMOD	0.00015140995
1,096	Interpretable and Informative Explanations of Outcomes	2015	VLDB	0.00014088686
1,106	Provenance for Aggregate Queries	2011	PODS	0.00013976386
1,119	The Complexity of Causality and Responsibility for Query Answers and non-Answers	2011	VLDB	0.00013851012
1,124	How to ConQueR Why-Not Questions	2010	SIGMOD	0.00013832959
1,566	PrivBasis: Frequent Itemset Mining with Differential Privacy	2012	VLDB	0.00011324162
1,740	PrivateSQL: A Differentially Private SQL Query Engine	2019	VLDB	0.00010696383
2,436	Optimizing error of high-dimensional statistical queries under differential privacy	2018	VLDB	8.8217855e-05
2,565	Explaining Missing Answers to SPJUA Queries	2010	VLDB	8.5307653e-05
2,600	Tracing Data Errors with View-Conditioned Causality	2011	SIGMOD	8.4652308e-05
2,655	Explaining Query Answers with Explanation-Ready Databases	2016	VLDB	8.3638668e-05
3,030	The Impact of Negation on the Complexity of the Shapley Value in Conjunctive Queries	2020	PODS	7.676832e-05
3,083	Computing Local Sensitivities of Counting Queries with Joins	2020	SIGMOD	7.5985351e-05
3,158	Fine-Grained, Secure and Efficient Data Provenance on Blockchain Systems	2019	VLDB	7.466958e-05
3,401	Answering Range Queries Under Local Differential Privacy	2019	VLDB	7.1343786e-05
5,192	Going Beyond Provenance: Explaining Query Answers with Pattern-based Counterbalances	2019	SIGMOD	5.6324589e-05
5,499	R2T: Instance-optimal Truncation for Differentially Private Query Evaluation with Foreign Keys	2022	SIGMOD	5.4737427e-05
5,706	Putting Things into Context: Rich Explanations for Query Answers using Join Graphs	2021	SIGMOD	5.3633001e-05
5,773	Mining Frequent Patterns with Differential Privacy	2013	VLDB	5.3300095e-05
5,877	Differential Privacy and the US Census	2019	PODS	5.2886439e-05
6,511	Provenance Views for Module Privacy	2011	PODS	5.0273291e-05
6,969	Architecting a Differentially Private SQL Engine	2019	CIDR	4.8749348e-05
7,059	Residual Sensitivity for Differentially Private Multi-Way Joins	2021	SIGMOD	4.8404261e-05
7,131	Enabling Privacy in Provenance-Aware Workflow Systems	2011	CIDR	4.8181343e-05
7,584	A Nearly Instance-optimal Differentially Private Mechanism for Conjunctive Queries	2022	PODS	4.7015411e-05
11,474	On Optimizing the Trade-off between Privacy and Utility in Data Provenance	2021	SIGMOD	4.1905499e-05

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Overall Rank	Paper	Year	Venue	Pagerank
1,740	PrivateSQL: A Differentially Private SQL Query Engine	2019	VLDB	0.00010696383
11,115	DOP-SQL: A General-purpose, High-utility, and Extensible Private SQL System	2024	VLDB	4.1905499e-05
451	Towards Practical Differential Privacy for SQL Queries	2018	VLDB	0.00022807098
10,041	A General Framework for Per-record Differential Privacy	2026	SIGMOD	4.1905499e-05
2,461	Principled Evaluation of Differentially Private Algorithms using DPBench	2016	SIGMOD	8.7486072e-05
8,837	Cache Me If You Can: Accuracy-Aware Inference Engine for Differentially Private Data Exploration	2023	VLDB	4.4350633e-05
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13,113	Demonstration of DPClustX: Differentially Private Explanations for Clusters	2025	SIGMOD	-
10,015	Differentially Private Explanations for Clusters	2026	SIGMOD	4.1905499e-05
11,283	Explaining Differentially Private Query Results With DPXPlain	2023	VLDB	4.1905499e-05